Mood and Stress Evaluation of Adult Patients With Moyamoya Disease in Korea: Ecological Momentary Assessment Method Using a Mobile Phone App
Bibliographic record
Abstract
BACKGROUND: Moyamoya disease (MMD) is a known progressive obstructive cerebrovascular disorder. Monitoring and managing mood and stress are critical for patients with MMD, as they affect clinical outcomes. The ecological momentary assessment (EMA) method is a longitudinal study design by which multiple variable assessments can be performed over time to detect momentary fluctuations and changes in psychological dimensions such as mood and stress over time. OBJECTIVE: This study aimed to identify predicting factors associated with momentary mood and stress at both the within-person and between-person levels and to examine individual fluctuation of mood over time in the short term using an EMA method combined with a mobile phone app. METHODS: Participants aged older than 18 years were recruited from a tertiary hospital in Seoul, Korea, between July 2018 and January 2019. The PsyMate scale for negative affect (NA) and positive affect (PA) and the Trier Inventory for Chronic Stress Scale were uploaded on patient mobile phones. Using a mobile app, data were collected four times a day for 7 days. Pearson correlations and mixed modeling were used to predict relationships between repeatedly measured variables at both the between-person and within-person levels. RESULTS: The mean age of the 93 participants was 40.59 (SD 10.06) years, 66 (71%) were female, and 71 (76%) were married. Participants provided 1929 responses out of a possible 2604 responses (1929/2604, 74.08%). The mean momentary NA and PA values were 2.15 (SD 1.12) and 4.70 (SD 1.31) out of 7, respectively. The momentary stress value was 2.03 (SD 0.98) out of 5. Momentary NA, PA, and stress were correlated (P<.001) and varied over time in relation to momentary variables. Common momentary variables associated with momentary mood and stress at both the within-person (level 1) and between-person (level 2) levels were identified. Momentary NA increased when being alone and being at the hospital at both levels, whereas momentary PA increased when eating or drinking, resting, being at a café, restaurant or a public place but decreased when being alone at both levels. Momentary stress increased when being at the office, at a public place, or as the time of the day went by but decreased when resting or during the weekend. Different factors affecting mood and stress at different levels were identified. Fluctuations in individual momentary mood over time at the within-person level were captured. CONCLUSIONS: The EMA method using a mobile phone app demonstrated its ability to capture changes in mood and stress in various environmental contexts in patients with MMD. The results could provide baseline information for developing interventions to manage negative mood and stress of patients with MMD based on the identified predictors affecting mood and stress at two different levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".